GOLEM: Automated and Robust Cryo-EM-Guided Ligand Docking with Explicit Water Molecules

Abstract

A detailed understanding of ligand-protein interactions underpins rational drug-design strategies. In recent years, technological advances in cryo-electron microscopy (cryo-EM) brought a new era for the structural determination of biological macromolecules and assemblies at a high resolution, marking cryo-EM a promising tool for studying ligand-protein interactions. However, even in high-resolution cryo-EM structures, the bound ligand's densities are often of lower quality due to its dynamic nature, frustrating an accurate coordinate assignment. Computational methods have been offering complementary efforts to aid structure modeling, such as MDFF (molecular dynamics flexible fitting) to fit atomic structures of macromolecules into corresponding cryo-EM densities. To address the challenge of ligand modeling in cryo-EM maps, here we report the development and validation of GOLEM (Genetic Optimization of Ligand in Experimental Maps), an automated and robust ligand docking method that models the ligand's optimal pose and conformation in cryo-EM maps. GOLEM employs a Lamarckian genetic algorithm, which performs a hybrid global/local search to explore the ligand's conformational, orientational, and positional space, with explicit consideration of water displacement and bridging water molecules' position and orientation. GOLEM takes into account both energetics and the correlation with the electron density maps in its scoring function, which is a combination of the system's energy and the energy of the ligand in a cryo-EM-derived external potential. GOLEM is validated in multiple cryo-EM structures with a wide range of map resolutions and ligand types, producing ligand poses in excellent agreement with the densities. As a VMD plugin, GOLEM is free-of-charge and accessible to the community. With these features, we believe GOLEM will be a valuable tool for ligand modeling in cryo-EM efforts towards drug discoveries.